Фото: Пелагия Тихонова / РИА Новости
单摄像头、老旧的 USB 2.0 接口,至于机身正面长什么样,目前的爆料分成了两派:有说继续用刘海,也有说灵动岛终于要下放了。不过,纠结形态其实意义不大,因为无论额头怎么切,所有线索最终都指向了一个最熟悉、也最无奈的现实:iPhone 17e 依旧使用一块 60Hz 的屏幕。
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Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.